Open-source generation of sigma profiles: impact of quantum chemistry and solvation treatment on machine learning performance
The open-source generation of Sigma Profiles (SPs) using OpenSPGen was tuned to maximize machine learning performance and minimize computational cost.
Authors
- Dinis O. Abranches (ORCID: https://orcid.org/0000-0003-0097-2072)
- Fathya Y. M. Salih (ORCID: https://orcid.org/0000-0002-8731-9393)
- Edward Joseph Maginn (ORCID: https://orcid.org/0000-0002-6309-1347)
- Yamil J. Colón (ORCID: https://orcid.org/0000-0001-5316-9692)
Institutions
- University of Notre Dame (US)
- University of Aveiro (PT)
Publication Details
- Journal
- Digital Discovery
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5dd00087d
- Citations
- 3
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 1.55
Funders
- National Science Foundation
- U.S. Department of Energy
- Ministério da Ciência, Tecnologia e Ensino Superior
- Office of Science
- Centro de Investigação em Materiais Cerâmicos e Compósitos
- Fundação para a Ciência e a Tecnologia
- Basic Energy Sciences
- Los Alamos National Laboratory
- Institute for Materials Science, Los Alamos National Laboratory